Register to reserve your spot

Date and Time

April 25, 2025 from 5:30 PM to 8:30 PM

Location

The Meetup will take place at MotionLab.Berlin, Bouchéstraße 12/Halle 20 in Berlin

Leaving No Pixels Behind: Deep Learning for Perfect Cutouts

Removing backgrounds from images is a challenging task, even for advanced deep learning models. The human eye is highly sensitive to minor imperfections, making high-quality outcomes crucial. In this talk, Imran Kocabiyik will demonstrate how withoutbg achieves clean, natural-looking image extractions while addressing the issues of costly training data and the need to handle diverse image types. Their approach effectively balances intelligent model design and meticulous data selection, resulting in impressive performance suited for real-world applications.

About the Speaker

Imran Kocabiyik is a technologist building AI-driven tools for marketing and creative automation. He is the founder of withoutbg and a Senior Data Scientist at Klarna.

AI on the Dance Floor: Multimodal Segmentation of Choreography Videos

Ever struggled to learn a dance routine by constantly rewinding YouTube videos? In this talk, Paras presents an approach based on temporal convolutional networks and pose estimation to automatically segment choreography videos into individual moves by leveraging both audio and visual modalities.

About the Speaker

Dr. Paras Mehta is a computer scientist and co-founder of sylby, where he leads AI engineering for pronunciation training and language learning applications.

When Images Look Alike: Intro to Dataset Curation

This talk introduces dataset curation in computer vision, focusing on visually similar images. We discuss use cases in vacation rental search and art recommendations. We demonstrate how Voxel51 helps identify image similarity, improving data quality and model reliability.

About the Speaker

Antonio Rueda-Toicen, an AI Engineer in Berlin, has extensive experience in deploying machine learning models and has taught over 300 professionals. He is currently a Research Scientist at the Hasso Plattner Institute. Since 2019, he has organized the Berlin Computer Vision Group and taught at Berlin’s Data Science Retreat. He specializes in computer vision, cloud technologies, and machine learning. Antonio is also a certified instructor of deep learning and diffusion models in NVIDIA’s Deep Learning Institute.

EnvisionHGdetector: A Framework for Detecting and Analyzing Hand Gestures During Speech

We present EnvisionHGdetector, a toolkit for studying hand movements during speech. It measures hand motion, compares gestures, and labels gesture segments using Mediapipe tracking and a custom neural network. Tested on over 8,000 gestures, it achieved approximately 75% accuracy. We also discuss plans to improve accessibility for gesture researchers.

About the Speaker

Sharjeel Shaikh is currently pursuing an MSc in Data Science at the University of Potsdam. He works at HPI on Gesture Detection and Data Masking.